def as_real_imag(self, deep=True, **hints):
from sympy.core.symbol import symbols
from sympy.polys.polytools import poly
from sympy.core.function import expand_multinomial
if self.exp.is_Integer:
exp = self.exp
re, im = self.base.as_real_imag(deep=deep)
if re.func == C.re or im.func == C.im:
return self, S.Zero
a, b = symbols('a b', cls=Dummy)
if exp >= 0:
if re.is_Number and im.is_Number:
# We can be more efficient in this case
expr = expand_multinomial(self.base**exp)
return expr.as_real_imag()
expr = poly((a + b)**exp) # a = re, b = im; expr = (a + b*I)**exp
else:
mag = re**2 + im**2
re, im = re/mag, -im/mag
if re.is_Number and im.is_Number:
# We can be more efficient in this case
expr = expand_multinomial((re + im*S.ImaginaryUnit)**-exp)
return expr.as_real_imag()
expr = poly((a + b)**-exp)
# Terms with even b powers will be real
r = [i for i in expr.terms() if not i[0][1] % 2]
re_part = Add(*[cc*a**aa*b**bb for (aa, bb), cc in r])
# Terms with odd b powers will be imaginary
r = [i for i in expr.terms() if i[0][1] % 4 == 1]
im_part1 = Add(*[cc*a**aa*b**bb for (aa, bb), cc in r])
r = [i for i in expr.terms() if i[0][1] % 4 == 3]
im_part3 = Add(*[cc*a**aa*b**bb for (aa, bb), cc in r])
return (re_part.subs({a: re, b: S.ImaginaryUnit*im}),
im_part1.subs({a: re, b: im}) + im_part3.subs({a: re, b: -im}))
elif self.exp.is_Rational:
# NOTE: This is not totally correct since for x**(p/q) with
# x being imaginary there are actually q roots, but
# only a single one is returned from here.
re, im = self.base.as_real_imag(deep=deep)
if re.func == C.re or im.func == C.im:
return self, S.Zero
r = Pow(Pow(re, 2) + Pow(im, 2), S.Half)
t = C.atan2(im, re)
rp, tp = Pow(r, self.exp), t*self.exp
return (rp*C.cos(tp), rp*C.sin(tp))
else:
if deep:
hints['complex'] = False
return (C.re(self.expand(deep, **hints)),
C.im(self.expand(deep, **hints)))
else:
return (C.re(self), C.im(self))
def test_issues_5919_6830():
# issue 5919
n = -1 + 1 / x
z = n / x / (-n) ** 2 - 1 / n / x
assert expand(z) == 1 / (x ** 2 - 2 * x + 1) - 1 / (x - 2 + 1 / x) - 1 / (-x + 1)
# issue 6830
p = (1 + x) ** 2
assert expand_multinomial((1 + x * p) ** 2) == (
x ** 2 * (x ** 4 + 4 * x ** 3 + 6 * x ** 2 + 4 * x + 1) + 2 * x * (x ** 2 + 2 * x + 1) + 1
)
assert expand_multinomial((1 + (y + x) * p) ** 2) == (
2 * ((x + y) * (x ** 2 + 2 * x + 1))
+ (x ** 2 + 2 * x * y + y ** 2) * (x ** 4 + 4 * x ** 3 + 6 * x ** 2 + 4 * x + 1)
+ 1
)
A = Symbol("A", commutative=False)
p = (1 + A) ** 2
assert expand_multinomial((1 + x * p) ** 2) == (
x ** 2 * (1 + 4 * A + 6 * A ** 2 + 4 * A ** 3 + A ** 4) + 2 * x * (1 + 2 * A + A ** 2) + 1
)
assert expand_multinomial((1 + (y + x) * p) ** 2) == (
(x + y) * (1 + 2 * A + A ** 2) * 2
+ (x ** 2 + 2 * x * y + y ** 2) * (1 + 4 * A + 6 * A ** 2 + 4 * A ** 3 + A ** 4)
+ 1
)
assert expand_multinomial((1 + (y + x) * p) ** 3) == (
(x + y) * (1 + 2 * A + A ** 2) * 3
+ (x ** 2 + 2 * x * y + y ** 2) * (1 + 4 * A + 6 * A ** 2 + 4 * A ** 3 + A ** 4) * 3
+ (x ** 3 + 3 * x ** 2 * y + 3 * x * y ** 2 + y ** 3)
* (1 + 6 * A + 15 * A ** 2 + 20 * A ** 3 + 15 * A ** 4 + 6 * A ** 5 + A ** 6)
+ 1
)
# unevaluate powers
eq = Pow((x + 1) * ((A + 1) ** 2), 2, evaluate=False)
# - in this case the base is not an Add so no further
# expansion is done
assert expand_multinomial(eq) == (x ** 2 + 2 * x + 1) * (1 + 4 * A + 6 * A ** 2 + 4 * A ** 3 + A ** 4)
# - but here, the expanded base *is* an Add so it gets expanded
eq = Pow(((A + 1) ** 2), 2, evaluate=False)
assert expand_multinomial(eq) == 1 + 4 * A + 6 * A ** 2 + 4 * A ** 3 + A ** 4
# coverage
def ok(a, b, n):
e = (a + I * b) ** n
return verify_numerically(e, expand_multinomial(e))
for a in [2, S.Half]:
for b in [3, S(1) / 3]:
for n in range(2, 6):
assert ok(a, b, n)
assert expand_multinomial((x + 1 + O(z)) ** 2) == 1 + 2 * x + x ** 2 + O(z)
assert expand_multinomial((x + 1 + O(z)) ** 3) == 1 + 3 * x + 3 * x ** 2 + x ** 3 + O(z)
assert expand_multinomial(3 ** (x + y + 3)) == 27 * 3 ** (x + y)
def test_better_sqrt():
n = Symbol('n', integer=True, nonnegative=True)
assert sqrt(3 + 4*I) == 2 + I
assert sqrt(3 - 4*I) == 2 - I
assert sqrt(-3 - 4*I) == 1 - 2*I
assert sqrt(-3 + 4*I) == 1 + 2*I
assert sqrt(32 + 24*I) == 6 + 2*I
assert sqrt(32 - 24*I) == 6 - 2*I
assert sqrt(-32 - 24*I) == 2 - 6*I
assert sqrt(-32 + 24*I) == 2 + 6*I
# triple (3, 4, 5):
# parity of 3 matches parity of 5 and
# den, 4, is a square
assert sqrt((3 + 4*I)/4) == 1 + I/2
# triple (8, 15, 17)
# parity of 8 doesn't match parity of 17 but
# den/2, 8/2, is a square
assert sqrt((8 + 15*I)/8) == (5 + 3*I)/4
# handle the denominator
assert sqrt((3 - 4*I)/25) == (2 - I)/5
assert sqrt((3 - 4*I)/26) == (2 - I)/sqrt(26)
# mul
# issue #12739
assert sqrt((3 + 4*I)/(3 - 4*I)) == (3 + 4*I)/5
assert sqrt(2/(3 + 4*I)) == sqrt(2)/5*(2 - I)
assert sqrt(n/(3 + 4*I)).subs(n, 2) == sqrt(2)/5*(2 - I)
assert sqrt(-2/(3 + 4*I)) == sqrt(2)/5*(1 + 2*I)
assert sqrt(-n/(3 + 4*I)).subs(n, 2) == sqrt(2)/5*(1 + 2*I)
# power
assert sqrt(1/(3 + I*4)) == (2 - I)/5
assert sqrt(1/(3 - I)) == sqrt(10)*sqrt(3 + I)/10
# symbolic
i = symbols('i', imaginary=True)
assert sqrt(3/i) == Mul(sqrt(3), sqrt(-i)/abs(i), evaluate=False)
# multiples of 1/2; don't make this too automatic
assert sqrt((3 + 4*I))**3 == (2 + I)**3
assert Pow(3 + 4*I, S(3)/2) == 2 + 11*I
assert Pow(6 + 8*I, S(3)/2) == 2*sqrt(2)*(2 + 11*I)
n, d = (3 + 4*I), (3 - 4*I)**3
a = n/d
assert a.args == (1/d, n)
eq = sqrt(a)
assert eq.args == (a, S.Half)
assert expand_multinomial(eq) == sqrt((-117 + 44*I)*(3 + 4*I))/125
assert eq.expand() == (7 - 24*I)/125
# issue 12775
# pos im part
assert sqrt(2*I) == (1 + I)
assert sqrt(2*9*I) == Mul(3, 1 + I, evaluate=False)
assert Pow(2*I, 3*S.Half) == (1 + I)**3
# neg im part
assert sqrt(-I/2) == Mul(S.Half, 1 - I, evaluate=False)
# fractional im part
assert Pow(-9*I/2, 3/S(2)) == 27*(1 - I)**3/8
def _eval_power(self, e):
if e.is_Rational and self.is_number:
from sympy.core.evalf import pure_complex
from sympy.core.mul import _unevaluated_Mul
from sympy.core.exprtools import factor_terms
from sympy.core.function import expand_multinomial
from sympy.functions.elementary.complexes import sign
from sympy.functions.elementary.miscellaneous import sqrt
ri = pure_complex(self)
if ri:
r, i = ri
if e.q == 2:
D = sqrt(r**2 + i**2)
if D.is_Rational:
# (r, i, D) is a Pythagorean triple
root = sqrt(factor_terms((D - r)/2))**e.p
return root*expand_multinomial((
# principle value
(D + r)/abs(i) + sign(i)*S.ImaginaryUnit)**e.p)
elif e == -1:
return _unevaluated_Mul(
r - i*S.ImaginaryUnit,
1/(r**2 + i**2))
def as_real_imag(self, deep=True, **hints):
from sympy.polys.polytools import poly
if self.exp.is_Integer:
exp = self.exp
re, im = self.base.as_real_imag(deep=deep)
if not im:
return self, S.Zero
a, b = symbols('a b', cls=Dummy)
if exp >= 0:
if re.is_Number and im.is_Number:
# We can be more efficient in this case
expr = expand_multinomial(self.base**exp)
return expr.as_real_imag()
expr = poly(
(a + b)**exp) # a = re, b = im; expr = (a + b*I)**exp
else:
mag = re**2 + im**2
re, im = re/mag, -im/mag
if re.is_Number and im.is_Number:
# We can be more efficient in this case
expr = expand_multinomial((re + im*S.ImaginaryUnit)**-exp)
return expr.as_real_imag()
expr = poly((a + b)**-exp)
# Terms with even b powers will be real
r = [i for i in expr.terms() if not i[0][1] % 2]
re_part = Add(*[cc*a**aa*b**bb for (aa, bb), cc in r])
# Terms with odd b powers will be imaginary
r = [i for i in expr.terms() if i[0][1] % 4 == 1]
im_part1 = Add(*[cc*a**aa*b**bb for (aa, bb), cc in r])
r = [i for i in expr.terms() if i[0][1] % 4 == 3]
im_part3 = Add(*[cc*a**aa*b**bb for (aa, bb), cc in r])
return (re_part.subs({a: re, b: S.ImaginaryUnit*im}),
im_part1.subs({a: re, b: im}) + im_part3.subs({a: re, b: -im}))
elif self.exp.is_Rational:
re, im = self.base.as_real_imag(deep=deep)
if im.is_zero and self.exp is S.Half:
if re.is_nonnegative:
return self, S.Zero
if re.is_nonpositive:
return S.Zero, (-self.base)**self.exp
# XXX: This is not totally correct since for x**(p/q) with
# x being imaginary there are actually q roots, but
# only a single one is returned from here.
r = self.func(self.func(re, 2) + self.func(im, 2), S.Half)
t = C.atan2(im, re)
rp, tp = self.func(r, self.exp), t*self.exp
return (rp*C.cos(tp), rp*C.sin(tp))
else:
if deep:
hints['complex'] = False
expanded = self.expand(deep, **hints)
if hints.get('ignore') == expanded:
return None
else:
return (C.re(expanded), C.im(expanded))
else:
return (C.re(self), C.im(self))
def _eval_expand_multinomial(self, **hints):
"""(a+b+..) ** n -> a**n + n*a**(n-1)*b + .., n is nonzero integer"""
base, exp = self.args
result = self
if exp.is_Rational and exp.p > 0 and base.is_Add:
if not exp.is_Integer:
n = Integer(exp.p // exp.q)
if not n:
return result
else:
radical, result = self.func(base, exp - n), []
expanded_base_n = self.func(base, n)
if expanded_base_n.is_Pow:
expanded_base_n = \
expanded_base_n._eval_expand_multinomial()
for term in Add.make_args(expanded_base_n):
result.append(term*radical)
return Add(*result)
n = int(exp)
if base.is_commutative:
order_terms, other_terms = [], []
for b in base.args:
if b.is_Order:
order_terms.append(b)
else:
other_terms.append(b)
if order_terms:
# (f(x) + O(x^n))^m -> f(x)^m + m*f(x)^{m-1} *O(x^n)
f = Add(*other_terms)
o = Add(*order_terms)
if n == 2:
return expand_multinomial(f**n, deep=False) + n*f*o
else:
g = expand_multinomial(f**(n - 1), deep=False)
return expand_mul(f*g, deep=False) + n*g*o
if base.is_number:
# Efficiently expand expressions of the form (a + b*I)**n
# where 'a' and 'b' are real numbers and 'n' is integer.
a, b = base.as_real_imag()
if a.is_Rational and b.is_Rational:
if not a.is_Integer:
if not b.is_Integer:
k = self.func(a.q * b.q, n)
a, b = a.p*b.q, a.q*b.p
else:
k = self.func(a.q, n)
a, b = a.p, a.q*b
elif not b.is_Integer:
k = self.func(b.q, n)
a, b = a*b.q, b.p
else:
k = 1
a, b, c, d = int(a), int(b), 1, 0
while n:
if n & 1:
c, d = a*c - b*d, b*c + a*d
n -= 1
a, b = a*a - b*b, 2*a*b
n //= 2
I = S.ImaginaryUnit
if k == 1:
return c + I*d
else:
return Integer(c)/k + I*d/k
p = other_terms
# (x+y)**3 -> x**3 + 3*x**2*y + 3*x*y**2 + y**3
# in this particular example:
# p = [x,y]; n = 3
# so now it's easy to get the correct result -- we get the
# coefficients first:
from sympy import multinomial_coefficients
from sympy.polys.polyutils import basic_from_dict
expansion_dict = multinomial_coefficients(len(p), n)
# in our example: {(3, 0): 1, (1, 2): 3, (0, 3): 1, (2, 1): 3}
# and now construct the expression.
return basic_from_dict(expansion_dict, *p)
else:
if n == 2:
return Add(*[f*g for f in base.args for g in base.args])
else:
multi = (base**(n - 1))._eval_expand_multinomial()
if multi.is_Add:
return Add(*[f*g for f in base.args
for g in multi.args])
else:
# XXX can this ever happen if base was an Add?
return Add(*[f*multi for f in base.args])
elif (exp.is_Rational and exp.p < 0 and base.is_Add and
abs(exp.p) > exp.q):
return 1 / self.func(base, -exp)._eval_expand_multinomial()
elif exp.is_Add and base.is_Number:
# a + b a b
# n --> n n , where n, a, b are Numbers
coeff, tail = S.One, S.Zero
for term in exp.args:
if term.is_Number:
coeff *= self.func(base, term)
else:
tail += term
return coeff * self.func(base, tail)
else:
return result
def _mexpand(expr):
return expand_mul(expand_multinomial(expr))
def _minpoly_groebner(ex, x, cls):
"""
Computes the minimal polynomial of an algebraic number
using Groebner bases
Examples
========
>>> from sympy import minimal_polynomial, sqrt, Rational
>>> from sympy.abc import x
>>> minimal_polynomial(sqrt(2) + 3*Rational(1, 3), x, compose=False)
x**2 - 2*x - 1
"""
generator = numbered_symbols('a', cls=Dummy)
mapping, symbols = {}, {}
def update_mapping(ex, exp, base=None):
a = next(generator)
symbols[ex] = a
if base is not None:
mapping[ex] = a**exp + base
else:
mapping[ex] = exp.as_expr(a)
return a
def bottom_up_scan(ex):
"""
Transform a given algebraic expression *ex* into a multivariate
polynomial, by introducing fresh variables with defining equations.
Explanation
===========
The critical elements of the algebraic expression *ex* are root
extractions, instances of :py:class:`~.AlgebraicNumber`, and negative
powers.
When we encounter a root extraction or an :py:class:`~.AlgebraicNumber`
we replace this expression with a fresh variable ``a_i``, and record
the defining polynomial for ``a_i``. For example, if ``a_0**(1/3)``
occurs, we will replace it with ``a_1``, and record the new defining
polynomial ``a_1**3 - a_0``.
When we encounter a negative power we transform it into a positive
power by algebraically inverting the base. This means computing the
minimal polynomial in ``x`` for the base, inverting ``x`` modulo this
poly (which generates a new polynomial) and then substituting the
original base expression for ``x`` in this last polynomial.
We return the transformed expression, and we record the defining
equations for new symbols using the ``update_mapping()`` function.
"""
if ex.is_Atom:
if ex is S.ImaginaryUnit:
if ex not in mapping:
return update_mapping(ex, 2, 1)
else:
return symbols[ex]
elif ex.is_Rational:
return ex
elif ex.is_Add:
return Add(*[bottom_up_scan(g) for g in ex.args])
elif ex.is_Mul:
return Mul(*[bottom_up_scan(g) for g in ex.args])
elif ex.is_Pow:
if ex.exp.is_Rational:
if ex.exp < 0:
minpoly_base = _minpoly_groebner(ex.base, x, cls)
inverse = invert(x, minpoly_base).as_expr()
base_inv = inverse.subs(x, ex.base).expand()
if ex.exp == -1:
return bottom_up_scan(base_inv)
else:
ex = base_inv**(-ex.exp)
if not ex.exp.is_Integer:
base, exp = (ex.base**ex.exp.p).expand(), Rational(
1, ex.exp.q)
else:
base, exp = ex.base, ex.exp
base = bottom_up_scan(base)
expr = base**exp
if expr not in mapping:
if exp.is_Integer:
return expr.expand()
else:
return update_mapping(expr, 1 / exp, -base)
else:
return symbols[expr]
elif ex.is_AlgebraicNumber:
if ex not in mapping:
return update_mapping(ex, ex.minpoly_of_element())
else:
return symbols[ex]
raise NotAlgebraic("%s doesn't seem to be an algebraic number" % ex)
def simpler_inverse(ex):
"""
Returns True if it is more likely that the minimal polynomial
algorithm works better with the inverse
"""
if ex.is_Pow:
if (1 / ex.exp).is_integer and ex.exp < 0:
if ex.base.is_Add:
return True
if ex.is_Mul:
hit = True
for p in ex.args:
if p.is_Add:
return False
if p.is_Pow:
if p.base.is_Add and p.exp > 0:
return False
if hit:
return True
return False
inverted = False
ex = expand_multinomial(ex)
if ex.is_AlgebraicNumber:
return ex.minpoly_of_element().as_expr(x)
elif ex.is_Rational:
result = ex.q * x - ex.p
else:
inverted = simpler_inverse(ex)
if inverted:
ex = ex**-1
res = None
if ex.is_Pow and (1 / ex.exp).is_Integer:
n = 1 / ex.exp
res = _minimal_polynomial_sq(ex.base, n, x)
elif _is_sum_surds(ex):
res = _minimal_polynomial_sq(ex, S.One, x)
if res is not None:
result = res
if res is None:
bus = bottom_up_scan(ex)
F = [x - bus] + list(mapping.values())
G = groebner(F, list(symbols.values()) + [x], order='lex')
_, factors = factor_list(G[-1])
# by construction G[-1] has root `ex`
result = _choose_factor(factors, x, ex)
if inverted:
result = _invertx(result, x)
if result.coeff(x**degree(result, x)) < 0:
result = expand_mul(-result)
return result
def _eval_expand_multinomial(self, **hints):
"""(a+b+..) ** n -> a**n + n*a**(n-1)*b + .., n is nonzero integer"""
base, exp = self.args
result = self
if exp.is_Rational and exp.p > 0 and base.is_Add:
if not exp.is_Integer:
n = Integer(exp.p // exp.q)
if not n:
return result
else:
radical, result = self.func(base, exp - n), []
expanded_base_n = self.func(base, n)
if expanded_base_n.is_Pow:
expanded_base_n = \
expanded_base_n._eval_expand_multinomial()
for term in Add.make_args(expanded_base_n):
result.append(term*radical)
return Add(*result)
n = int(exp)
if base.is_commutative:
order_terms, other_terms = [], []
for b in base.args:
if b.is_Order:
order_terms.append(b)
else:
other_terms.append(b)
if order_terms:
# (f(x) + O(x^n))^m -> f(x)^m + m*f(x)^{m-1} *O(x^n)
f = Add(*other_terms)
o = Add(*order_terms)
if n == 2:
return expand_multinomial(f**n, deep=False) + n*f*o
else:
g = expand_multinomial(f**(n - 1), deep=False)
return expand_mul(f*g, deep=False) + n*g*o
if base.is_number:
# Efficiently expand expressions of the form (a + b*I)**n
# where 'a' and 'b' are real numbers and 'n' is integer.
a, b = base.as_real_imag()
if a.is_Rational and b.is_Rational:
if not a.is_Integer:
if not b.is_Integer:
k = self.func(a.q * b.q, n)
a, b = a.p*b.q, a.q*b.p
else:
k = self.func(a.q, n)
a, b = a.p, a.q*b
elif not b.is_Integer:
k = self.func(b.q, n)
a, b = a*b.q, b.p
else:
k = 1
a, b, c, d = int(a), int(b), 1, 0
while n:
if n & 1:
c, d = a*c - b*d, b*c + a*d
n -= 1
a, b = a*a - b*b, 2*a*b
n //= 2
I = S.ImaginaryUnit
if k == 1:
return c + I*d
else:
return Integer(c)/k + I*d/k
p = other_terms
# (x+y)**3 -> x**3 + 3*x**2*y + 3*x*y**2 + y**3
# in this particular example:
# p = [x,y]; n = 3
# so now it's easy to get the correct result -- we get the
# coefficients first:
from sympy import multinomial_coefficients
from sympy.polys.polyutils import basic_from_dict
expansion_dict = multinomial_coefficients(len(p), n)
# in our example: {(3, 0): 1, (1, 2): 3, (0, 3): 1, (2, 1): 3}
# and now construct the expression.
return basic_from_dict(expansion_dict, *p)
else:
if n == 2:
return Add(*[f*g for f in base.args for g in base.args])
else:
multi = (base**(n - 1))._eval_expand_multinomial()
if multi.is_Add:
return Add(*[f*g for f in base.args
for g in multi.args])
else:
# XXX can this ever happen if base was an Add?
return Add(*[f*multi for f in base.args])
elif (exp.is_Rational and exp.p < 0 and base.is_Add and
abs(exp.p) > exp.q):
return 1 / self.func(base, -exp)._eval_expand_multinomial()
elif exp.is_Add and base.is_Number:
# a + b a b
# n --> n n , where n, a, b are Numbers
coeff, tail = S.One, S.Zero
for term in exp.args:
if term.is_Number:
coeff *= self.func(base, term)
else:
tail += term
return coeff * self.func(base, tail)
else:
return result
def _mexpand(expr):
return expand_mul(expand_multinomial(expr))
def ok(a, b, n):
e = (a + I*b)**n
return verify_numerically(e, expand_multinomial(e))
def _eval_expand_multinomial(self, **hints):
"""(a+b+..) ** n -> a**n + n*a**(n-1)*b + .., n is nonzero integer"""
b = self.base
e = self.exp
if b is None:
base = self.base
else:
base = b
if e is None:
exp = self.exp
else:
exp = e
if e is not None or b is not None:
result = Pow(base, exp)
if result.is_Pow:
base, exp = result.base, result.exp
else:
return result
else:
result = None
if exp.is_Rational and exp.p > 0 and base.is_Add:
if not exp.is_Integer:
n = Integer(exp.p // exp.q)
if not n:
return Pow(base, exp)
else:
radical, result = Pow(base, exp - n), []
expanded_base_n = Pow(base, n)
if expanded_base_n.is_Pow:
expanded_base_n = \
expanded_base_n._eval_expand_multinomial()
for term in Add.make_args(expanded_base_n):
result.append(term * radical)
return Add(*result)
n = int(exp)
if base.is_commutative:
order_terms, other_terms = [], []
for order in base.args:
if order.is_Order:
order_terms.append(order)
else:
other_terms.append(order)
if order_terms:
# (f(x) + O(x^n))^m -> f(x)^m + m*f(x)^{m-1} *O(x^n)
f = Add(*other_terms)
if n == 2:
return expand_multinomial(f**n, deep=False) + \
n*f*Add(*order_terms)
else:
g = expand_multinomial(f**(n - 1), deep=False)
return expand_mul(f*g, deep=False) + \
n*g*Add(*order_terms)
if base.is_number:
# Efficiently expand expressions of the form (a + b*I)**n
# where 'a' and 'b' are real numbers and 'n' is integer.
a, b = base.as_real_imag()
if a.is_Rational and b.is_Rational:
if not a.is_Integer:
if not b.is_Integer:
k = Pow(a.q * b.q, n)
a, b = a.p * b.q, a.q * b.p
else:
k = Pow(a.q, n)
a, b = a.p, a.q * b
elif not b.is_Integer:
k = Pow(b.q, n)
a, b = a * b.q, b.p
else:
k = 1
a, b, c, d = int(a), int(b), 1, 0
while n:
if n & 1:
c, d = a * c - b * d, b * c + a * d
n -= 1
a, b = a * a - b * b, 2 * a * b
n //= 2
I = S.ImaginaryUnit
if k == 1:
return c + I * d
else:
return Integer(c) / k + I * d / k
p = other_terms
# (x+y)**3 -> x**3 + 3*x**2*y + 3*x*y**2 + y**3
# in this particular example:
# p = [x,y]; n = 3
# so now it's easy to get the correct result -- we get the
# coefficients first:
from sympy import multinomial_coefficients
expansion_dict = multinomial_coefficients(len(p), n)
# in our example: {(3, 0): 1, (1, 2): 3, (0, 3): 1, (2, 1): 3}
# and now construct the expression.
# An elegant way would be to use Poly, but unfortunately it is
# slower than the direct method below, so it is commented out:
#b = {}
#for k in expansion_dict:
# b[k] = Integer(expansion_dict[k])
#return Poly(b, *p).as_expr()
from sympy.polys.polyutils import basic_from_dict
result = basic_from_dict(expansion_dict, *p)
return result
else:
if n == 2:
return Add(*[f * g for f in base.args for g in base.args])
else:
multi = (base**(n - 1))._eval_expand_multinomial()
if multi.is_Add:
return Add(
*[f * g for f in base.args for g in multi.args])
else:
return Add(*[f * multi for f in base.args])
elif (exp.is_Rational and exp.p < 0 and base.is_Add
and abs(exp.p) > exp.q):
return 1 / Pow(base, -exp)._eval_expand_multinomial()
elif exp.is_Add and base.is_Number:
# a + b a b
# n --> n n , where n, a, b are Numbers
coeff, tail = S.One, S.Zero
for term in exp.args:
if term.is_Number:
coeff *= Pow(base, term)
else:
tail += term
return coeff * Pow(base, tail)
else:
return result
def minimal_polynomial(ex, x=None, **args):
"""
Computes the minimal polynomial of an algebraic number.
Parameters
==========
ex : algebraic number expression
x : indipendent variable of the minimal polynomial
Options
=======
compose : if ``True`` _minpoly1`` is used, else the ``groebner`` algorithm
polys : if ``True`` returns a ``Poly`` object
Notes
=====
By default ``compose=True``, the minimal polynomial of the subexpressions of ``ex``
are computed, then the arithmetic operations on them are performed using the resultant
and factorization.
If ``compose=False``, a bottom-up algorithm is used with ``groebner``.
The default algorithm stalls less frequently.
Examples
========
>>> from sympy import minimal_polynomial, sqrt, solve
>>> from sympy.abc import x
>>> minimal_polynomial(sqrt(2), x)
x**2 - 2
>>> minimal_polynomial(sqrt(2) + sqrt(3), x)
x**4 - 10*x**2 + 1
>>> minimal_polynomial(solve(x**3 + x + 3)[0], x)
x**3 + x + 3
"""
from sympy.polys.polytools import degree
from sympy.core.function import expand_multinomial
from sympy.core.basic import preorder_traversal
compose = args.get('compose', True)
polys = args.get('polys', False)
ex = sympify(ex)
for expr in preorder_traversal(ex):
if expr.is_AlgebraicNumber:
compose = False
break
if ex.is_AlgebraicNumber:
compose = False
if x is not None:
x, cls = sympify(x), Poly
else:
x, cls = Dummy('x'), PurePoly
if compose:
result = _minpoly1(ex, x)
result = result.primitive()[1]
c = result.coeff(x**degree(result, x))
if c < 0:
result = expand_mul(-result)
c = -c
return cls(result, x, field=True) if polys else result
generator = numbered_symbols('a', cls=Dummy)
mapping, symbols, replace = {}, {}, []
def update_mapping(ex, exp, base=None):
a = generator.next()
symbols[ex] = a
if base is not None:
mapping[ex] = a**exp + base
else:
mapping[ex] = exp.as_expr(a)
return a
def bottom_up_scan(ex):
if ex.is_Atom:
if ex is S.ImaginaryUnit:
if ex not in mapping:
return update_mapping(ex, 2, 1)
else:
return symbols[ex]
elif ex.is_Rational:
return ex
elif ex.is_Add:
return Add(*[bottom_up_scan(g) for g in ex.args])
elif ex.is_Mul:
return Mul(*[bottom_up_scan(g) for g in ex.args])
elif ex.is_Pow:
if ex.exp.is_Rational:
if ex.exp < 0 and ex.base.is_Add:
coeff, terms = ex.base.as_coeff_add()
elt, _ = primitive_element(terms, polys=True)
alg = ex.base - coeff
# XXX: turn this into eval()
inverse = invert(elt.gen + coeff, elt).as_expr()
base = inverse.subs(elt.gen, alg).expand()
if ex.exp == -1:
return bottom_up_scan(base)
else:
ex = base**(-ex.exp)
if not ex.exp.is_Integer:
base, exp = (ex.base**ex.exp.p).expand(), Rational(
1, ex.exp.q)
else:
base, exp = ex.base, ex.exp
base = bottom_up_scan(base)
expr = base**exp
if expr not in mapping:
return update_mapping(expr, 1 / exp, -base)
else:
return symbols[expr]
elif ex.is_AlgebraicNumber:
if ex.root not in mapping:
return update_mapping(ex.root, ex.minpoly)
else:
return symbols[ex.root]
raise NotAlgebraic("%s doesn't seem to be an algebraic number" % ex)
def simpler_inverse(ex):
"""
Returns True if it is more likely that the minimal polynomial
algorithm works better with the inverse
"""
if ex.is_Pow:
if (1 / ex.exp).is_integer and ex.exp < 0:
if ex.base.is_Add:
return True
if ex.is_Mul:
hit = True
a = []
for p in ex.args:
if p.is_Add:
return False
if p.is_Pow:
if p.base.is_Add and p.exp > 0:
return False
if hit:
return True
return False
inverted = False
ex = expand_multinomial(ex)
if ex.is_AlgebraicNumber:
if not polys:
return ex.minpoly.as_expr(x)
else:
return ex.minpoly.replace(x)
elif ex.is_Rational:
result = ex.q * x - ex.p
else:
inverted = simpler_inverse(ex)
if inverted:
ex = ex**-1
res = None
if ex.is_Pow and (1 / ex.exp).is_Integer:
n = 1 / ex.exp
res = _minimal_polynomial_sq(ex.base, n, x)
elif _is_sum_surds(ex):
res = _minimal_polynomial_sq(ex, S.One, x)
if res is not None:
result = res
if res is None:
bus = bottom_up_scan(ex)
F = [x - bus] + mapping.values()
G = groebner(F, symbols.values() + [x], order='lex')
_, factors = factor_list(G[-1])
# by construction G[-1] has root `ex`
result = _choose_factor(factors, x, ex)
if inverted:
result = _invertx(result, x)
if result.coeff(x**degree(result, x)) < 0:
result = expand_mul(-result)
if polys:
return cls(result, x, field=True)
else:
return result
def minimal_polynomial(ex, x=None, **args):
"""
Computes the minimal polynomial of an algebraic number.
Parameters
==========
ex : algebraic number expression
x : indipendent variable of the minimal polynomial
Options
=======
compose : if ``True`` _minpoly1`` is used, else the ``groebner`` algorithm
polys : if ``True`` returns a ``Poly`` object
Notes
=====
By default ``compose=True``, the minimal polynomial of the subexpressions of ``ex``
are computed, then the arithmetic operations on them are performed using the resultant
and factorization.
If ``compose=False``, a bottom-up algorithm is used with ``groebner``.
The default algorithm stalls less frequently.
Examples
========
>>> from sympy import minimal_polynomial, sqrt, solve
>>> from sympy.abc import x
>>> minimal_polynomial(sqrt(2), x)
x**2 - 2
>>> minimal_polynomial(sqrt(2) + sqrt(3), x)
x**4 - 10*x**2 + 1
>>> minimal_polynomial(solve(x**3 + x + 3)[0], x)
x**3 + x + 3
"""
from sympy.polys.polytools import degree
from sympy.core.function import expand_multinomial
from sympy.core.basic import preorder_traversal
compose = args.get('compose', True)
polys = args.get('polys', False)
ex = sympify(ex)
for expr in preorder_traversal(ex):
if expr.is_AlgebraicNumber:
compose = False
break
if ex.is_AlgebraicNumber:
compose = False
if x is not None:
x, cls = sympify(x), Poly
else:
x, cls = Dummy('x'), PurePoly
if compose:
result = _minpoly1(ex, x)
result = result.primitive()[1]
c = result.coeff(x**degree(result, x))
if c < 0:
result = expand_mul(-result)
c = -c
return cls(result, x, field=True) if polys else result
generator = numbered_symbols('a', cls=Dummy)
mapping, symbols, replace = {}, {}, []
def update_mapping(ex, exp, base=None):
a = generator.next()
symbols[ex] = a
if base is not None:
mapping[ex] = a**exp + base
else:
mapping[ex] = exp.as_expr(a)
return a
def bottom_up_scan(ex):
if ex.is_Atom:
if ex is S.ImaginaryUnit:
if ex not in mapping:
return update_mapping(ex, 2, 1)
else:
return symbols[ex]
elif ex.is_Rational:
return ex
elif ex.is_Add:
return Add(*[ bottom_up_scan(g) for g in ex.args ])
elif ex.is_Mul:
return Mul(*[ bottom_up_scan(g) for g in ex.args ])
elif ex.is_Pow:
if ex.exp.is_Rational:
if ex.exp < 0 and ex.base.is_Add:
coeff, terms = ex.base.as_coeff_add()
elt, _ = primitive_element(terms, polys=True)
alg = ex.base - coeff
# XXX: turn this into eval()
inverse = invert(elt.gen + coeff, elt).as_expr()
base = inverse.subs(elt.gen, alg).expand()
if ex.exp == -1:
return bottom_up_scan(base)
else:
ex = base**(-ex.exp)
if not ex.exp.is_Integer:
base, exp = (
ex.base**ex.exp.p).expand(), Rational(1, ex.exp.q)
else:
base, exp = ex.base, ex.exp
base = bottom_up_scan(base)
expr = base**exp
if expr not in mapping:
return update_mapping(expr, 1/exp, -base)
else:
return symbols[expr]
elif ex.is_AlgebraicNumber:
if ex.root not in mapping:
return update_mapping(ex.root, ex.minpoly)
else:
return symbols[ex.root]
raise NotAlgebraic("%s doesn't seem to be an algebraic number" % ex)
def simpler_inverse(ex):
"""
Returns True if it is more likely that the minimal polynomial
algorithm works better with the inverse
"""
if ex.is_Pow:
if (1/ex.exp).is_integer and ex.exp < 0:
if ex.base.is_Add:
return True
if ex.is_Mul:
hit = True
a = []
for p in ex.args:
if p.is_Add:
return False
if p.is_Pow:
if p.base.is_Add and p.exp > 0:
return False
if hit:
return True
return False
inverted = False
ex = expand_multinomial(ex)
if ex.is_AlgebraicNumber:
if not polys:
return ex.minpoly.as_expr(x)
else:
return ex.minpoly.replace(x)
elif ex.is_Rational:
result = ex.q*x - ex.p
else:
inverted = simpler_inverse(ex)
if inverted:
ex = ex**-1
res = None
if ex.is_Pow and (1/ex.exp).is_Integer:
n = 1/ex.exp
res = _minimal_polynomial_sq(ex.base, n, x)
elif _is_sum_surds(ex):
res = _minimal_polynomial_sq(ex, S.One, x)
if res is not None:
result = res
if res is None:
bus = bottom_up_scan(ex)
F = [x - bus] + mapping.values()
G = groebner(F, symbols.values() + [x], order='lex')
_, factors = factor_list(G[-1])
# by construction G[-1] has root `ex`
result = _choose_factor(factors, x, ex)
if inverted:
result = _invertx(result, x)
if result.coeff(x**degree(result, x)) < 0:
result = expand_mul(-result)
if polys:
return cls(result, x, field=True)
else:
return result
def _minpoly_groebner(ex, x, cls):
"""
Computes the minimal polynomial of an algebraic number
using Groebner bases
Examples
========
>>> from sympy import minimal_polynomial, sqrt, Rational
>>> from sympy.abc import x
>>> minimal_polynomial(sqrt(2) + 3*Rational(1, 3), x, compose=False)
x**2 - 2*x - 1
"""
from sympy.polys.polytools import degree
from sympy.core.function import expand_multinomial
generator = numbered_symbols('a', cls=Dummy)
mapping, symbols, replace = {}, {}, []
def update_mapping(ex, exp, base=None):
a = next(generator)
symbols[ex] = a
if base is not None:
mapping[ex] = a**exp + base
else:
mapping[ex] = exp.as_expr(a)
return a
def bottom_up_scan(ex):
if ex.is_Atom:
if ex is S.ImaginaryUnit:
if ex not in mapping:
return update_mapping(ex, 2, 1)
else:
return symbols[ex]
elif ex.is_Rational:
return ex
elif ex.is_Add:
return Add(*[ bottom_up_scan(g) for g in ex.args ])
elif ex.is_Mul:
return Mul(*[ bottom_up_scan(g) for g in ex.args ])
elif ex.is_Pow:
if ex.exp.is_Rational:
if ex.exp < 0 and ex.base.is_Add:
coeff, terms = ex.base.as_coeff_add()
elt, _ = primitive_element(terms, polys=True)
alg = ex.base - coeff
# XXX: turn this into eval()
inverse = invert(elt.gen + coeff, elt).as_expr()
base = inverse.subs(elt.gen, alg).expand()
if ex.exp == -1:
return bottom_up_scan(base)
else:
ex = base**(-ex.exp)
if not ex.exp.is_Integer:
base, exp = (
ex.base**ex.exp.p).expand(), Rational(1, ex.exp.q)
else:
base, exp = ex.base, ex.exp
base = bottom_up_scan(base)
expr = base**exp
if expr not in mapping:
return update_mapping(expr, 1/exp, -base)
else:
return symbols[expr]
elif ex.is_AlgebraicNumber:
if ex.root not in mapping:
return update_mapping(ex.root, ex.minpoly)
else:
return symbols[ex.root]
raise NotAlgebraic("%s doesn't seem to be an algebraic number" % ex)
def simpler_inverse(ex):
"""
Returns True if it is more likely that the minimal polynomial
algorithm works better with the inverse
"""
if ex.is_Pow:
if (1/ex.exp).is_integer and ex.exp < 0:
if ex.base.is_Add:
return True
if ex.is_Mul:
hit = True
a = []
for p in ex.args:
if p.is_Add:
return False
if p.is_Pow:
if p.base.is_Add and p.exp > 0:
return False
if hit:
return True
return False
inverted = False
ex = expand_multinomial(ex)
if ex.is_AlgebraicNumber:
return ex.minpoly.as_expr(x)
elif ex.is_Rational:
result = ex.q*x - ex.p
else:
inverted = simpler_inverse(ex)
if inverted:
ex = ex**-1
res = None
if ex.is_Pow and (1/ex.exp).is_Integer:
n = 1/ex.exp
res = _minimal_polynomial_sq(ex.base, n, x)
elif _is_sum_surds(ex):
res = _minimal_polynomial_sq(ex, S.One, x)
if res is not None:
result = res
if res is None:
bus = bottom_up_scan(ex)
F = [x - bus] + list(mapping.values())
G = groebner(F, list(symbols.values()) + [x], order='lex')
_, factors = factor_list(G[-1])
# by construction G[-1] has root `ex`
result = _choose_factor(factors, x, ex)
if inverted:
result = _invertx(result, x)
if result.coeff(x**degree(result, x)) < 0:
result = expand_mul(-result)
return result
def _eval_expand_multinomial(self, **hints):
"""(a+b+..) ** n -> a**n + n*a**(n-1)*b + .., n is nonzero integer"""
b = self.base
e = self.exp
if b is None:
base = self.base
else:
base = b
if e is None:
exp = self.exp
else:
exp = e
if e is not None or b is not None:
result = Pow(base, exp)
if result.is_Pow:
base, exp = result.base, result.exp
else:
return result
else:
result = None
if exp.is_Rational and exp.p > 0 and base.is_Add:
if not exp.is_Integer:
n = Integer(exp.p // exp.q)
if not n:
return Pow(base, exp)
else:
radical, result = Pow(base, exp - n), []
expanded_base_n = Pow(base, n)
if expanded_base_n.is_Pow:
expanded_base_n = expanded_base_n._eval_expand_multinomial()
for term in Add.make_args(expanded_base_n):
result.append(term*radical)
return Add(*result)
n = int(exp)
if base.is_commutative:
order_terms, other_terms = [], []
for order in base.args:
if order.is_Order:
order_terms.append(order)
else:
other_terms.append(order)
if order_terms:
# (f(x) + O(x^n))^m -> f(x)^m + m*f(x)^{m-1} *O(x^n)
f = Add(*other_terms)
if n == 2:
return expand_multinomial(f**n, deep=False) + n*f*Add(*order_terms)
else:
g = expand_multinomial(f**(n - 1), deep=False)
return expand_mul(f*g, deep=False) + n*g*Add(*order_terms)
if base.is_number:
# Efficiently expand expressions of the form (a + b*I)**n
# where 'a' and 'b' are real numbers and 'n' is integer.
a, b = base.as_real_imag()
if a.is_Rational and b.is_Rational:
if not a.is_Integer:
if not b.is_Integer:
k = Pow(a.q * b.q, n)
a, b = a.p*b.q, a.q*b.p
else:
k = Pow(a.q, n)
a, b = a.p, a.q*b
elif not b.is_Integer:
k = Pow(b.q, n)
a, b = a*b.q, b.p
else:
k = 1
a, b, c, d = int(a), int(b), 1, 0
while n:
if n & 1:
c, d = a*c-b*d, b*c+a*d
n -= 1
a, b = a*a-b*b, 2*a*b
n //= 2
I = S.ImaginaryUnit
if k == 1:
return c + I*d
else:
return Integer(c)/k + I*d/k
p = other_terms
# (x+y)**3 -> x**3 + 3*x**2*y + 3*x*y**2 + y**3
# in this particular example:
# p = [x,y]; n = 3
# so now it's easy to get the correct result -- we get the
# coefficients first:
from sympy import multinomial_coefficients
expansion_dict = multinomial_coefficients(len(p), n)
# in our example: {(3, 0): 1, (1, 2): 3, (0, 3): 1, (2, 1): 3}
# and now construct the expression.
# An elegant way would be to use Poly, but unfortunately it is
# slower than the direct method below, so it is commented out:
#b = {}
#for k in expansion_dict:
# b[k] = Integer(expansion_dict[k])
#return Poly(b, *p).as_expr()
from sympy.polys.polyutils import basic_from_dict
result = basic_from_dict(expansion_dict, *p)
return result
else:
if n == 2:
return Add(*[f*g for f in base.args for g in base.args])
else:
multi = (base**(n-1))._eval_expand_multinomial()
if multi.is_Add:
return Add(*[f*g for f in base.args for g in multi.args])
else:
return Add(*[f*multi for f in base.args])
elif exp.is_Rational and exp.p < 0 and base.is_Add and abs(exp.p) > exp.q:
return 1 / Pow(base, -exp)._eval_expand_multinomial()
elif exp.is_Add and base.is_Number:
# a + b a b
# n --> n n , where n, a, b are Numbers
coeff, tail = S.One, S.Zero
for term in exp.args:
if term.is_Number:
coeff *= Pow(base, term)
else:
tail += term
return coeff * Pow(base, tail)
else:
return result
def _eval_nseries(self, x, n, logx):
# NOTE! This function is an important part of the gruntz algorithm
# for computing limits. It has to return a generalized power
# series with coefficients in C(log, log(x)). In more detail:
# It has to return an expression
# c_0*x**e_0 + c_1*x**e_1 + ... (finitely many terms)
# where e_i are numbers (not necessarily integers) and c_i are
# expressions involving only numbers, the log function, and log(x).
from sympy import powsimp, collect, exp, log, O, ceiling
b, e = self.args
if e.is_Integer:
if e > 0:
# positive integer powers are easy to expand, e.g.:
# sin(x)**4 = (x-x**3/3+...)**4 = ...
return expand_multinomial(self.func(b._eval_nseries(x, n=n,
logx=logx), e), deep=False)
elif e is S.NegativeOne:
# this is also easy to expand using the formula:
# 1/(1 + x) = 1 - x + x**2 - x**3 ...
# so we need to rewrite base to the form "1+x"
nuse = n
cf = 1
try:
ord = b.as_leading_term(x)
cf = C.Order(ord, x).getn()
if cf and cf.is_Number:
nuse = n + 2*ceiling(cf)
else:
cf = 1
except NotImplementedError:
pass
b_orig, prefactor = b, O(1, x)
while prefactor.is_Order:
nuse += 1
b = b_orig._eval_nseries(x, n=nuse, logx=logx)
prefactor = b.as_leading_term(x)
# express "rest" as: rest = 1 + k*x**l + ... + O(x**n)
rest = expand_mul((b - prefactor)/prefactor)
if rest.is_Order:
return 1/prefactor + rest/prefactor + O(x**n, x)
k, l = rest.leadterm(x)
if l.is_Rational and l > 0:
pass
elif l.is_number and l > 0:
l = l.evalf()
elif l == 0:
k = k.simplify()
if k == 0:
# if prefactor == w**4 + x**2*w**4 + 2*x*w**4, we need to
# factor the w**4 out using collect:
return 1/collect(prefactor, x)
else:
raise NotImplementedError()
else:
raise NotImplementedError()
if cf < 0:
cf = S.One/abs(cf)
try:
dn = C.Order(1/prefactor, x).getn()
if dn and dn < 0:
pass
else:
dn = 0
except NotImplementedError:
dn = 0
terms = [1/prefactor]
for m in xrange(1, ceiling((n - dn)/l*cf)):
new_term = terms[-1]*(-rest)
if new_term.is_Pow:
new_term = new_term._eval_expand_multinomial(
deep=False)
else:
new_term = expand_mul(new_term, deep=False)
terms.append(new_term)
terms.append(O(x**n, x))
return powsimp(Add(*terms), deep=True, combine='exp')
else:
# negative powers are rewritten to the cases above, for
# example:
# sin(x)**(-4) = 1/( sin(x)**4) = ...
# and expand the denominator:
nuse, denominator = n, O(1, x)
while denominator.is_Order:
denominator = (b**(-e))._eval_nseries(x, n=nuse, logx=logx)
nuse += 1
if 1/denominator == self:
return self
# now we have a type 1/f(x), that we know how to expand
return (1/denominator)._eval_nseries(x, n=n, logx=logx)
if e.has(Symbol):
return exp(e*log(b))._eval_nseries(x, n=n, logx=logx)
# see if the base is as simple as possible
bx = b
while bx.is_Pow and bx.exp.is_Rational:
bx = bx.base
if bx == x:
return self
# work for b(x)**e where e is not an Integer and does not contain x
# and hopefully has no other symbols
def e2int(e):
"""return the integer value (if possible) of e and a
flag indicating whether it is bounded or not."""
n = e.limit(x, 0)
unbounded = n.is_unbounded
if not unbounded:
# XXX was int or floor intended? int used to behave like floor
# so int(-Rational(1, 2)) returned -1 rather than int's 0
try:
n = int(n)
except TypeError:
#well, the n is something more complicated (like 1+log(2))
try:
n = int(n.evalf()) + 1 # XXX why is 1 being added?
except TypeError:
pass # hope that base allows this to be resolved
n = _sympify(n)
return n, unbounded
order = O(x**n, x)
ei, unbounded = e2int(e)
b0 = b.limit(x, 0)
if unbounded and (b0 is S.One or b0.has(Symbol)):
# XXX what order
if b0 is S.One:
resid = (b - 1)
if resid.is_positive:
return S.Infinity
elif resid.is_negative:
return S.Zero
raise ValueError('cannot determine sign of %s' % resid)
return b0**ei
if (b0 is S.Zero or b0.is_unbounded):
if unbounded is not False:
return b0**e # XXX what order
if not ei.is_number: # if not, how will we proceed?
raise ValueError(
'expecting numerical exponent but got %s' % ei)
nuse = n - ei
if e.is_real and e.is_positive:
lt = b.as_leading_term(x)
# Try to correct nuse (= m) guess from:
# (lt + rest + O(x**m))**e =
# lt**e*(1 + rest/lt + O(x**m)/lt)**e =
# lt**e + ... + O(x**m)*lt**(e - 1) = ... + O(x**n)
try:
cf = C.Order(lt, x).getn()
nuse = ceiling(n - cf*(e - 1))
except NotImplementedError:
pass
bs = b._eval_nseries(x, n=nuse, logx=logx)
terms = bs.removeO()
if terms.is_Add:
bs = terms
lt = terms.as_leading_term(x)
# bs -> lt + rest -> lt*(1 + (bs/lt - 1))
return ((self.func(lt, e) * self.func((bs/lt).expand(), e).nseries(
x, n=nuse, logx=logx)).expand() + order)
if bs.is_Add:
from sympy import O
# So, bs + O() == terms
c = Dummy('c')
res = []
for arg in bs.args:
if arg.is_Order:
arg = c*arg.expr
res.append(arg)
bs = Add(*res)
rv = (bs**e).series(x).subs(c, O(1, x))
rv += order
return rv
rv = bs**e
if terms != bs:
rv += order
return rv
# either b0 is bounded but neither 1 nor 0 or e is unbounded
# b -> b0 + (b-b0) -> b0 * (1 + (b/b0-1))
o2 = order*(b0**-e)
z = (b/b0 - 1)
o = O(z, x)
#r = self._compute_oseries3(z, o2, self.taylor_term)
if o is S.Zero or o2 is S.Zero:
unbounded = True
else:
if o.expr.is_number:
e2 = log(o2.expr*x)/log(x)
else:
e2 = log(o2.expr)/log(o.expr)
n, unbounded = e2int(e2)
if unbounded:
# requested accuracy gives infinite series,
# order is probably non-polynomial e.g. O(exp(-1/x), x).
r = 1 + z
else:
l = []
g = None
for i in xrange(n + 2):
g = self._taylor_term(i, z, g)
g = g.nseries(x, n=n, logx=logx)
l.append(g)
r = Add(*l)
return expand_mul(r*b0**e) + order
def ok(a, b, n):
e = (a + I*b)**n
return verify_numerically(e, expand_multinomial(e))
def _minpoly_groebner(ex, x, cls):
"""
Computes the minimal polynomial of an algebraic number
using Groebner bases
Examples
========
>>> from sympy import minimal_polynomial, sqrt, Rational
>>> from sympy.abc import x
>>> minimal_polynomial(sqrt(2) + 3*Rational(1, 3), x, compose=False)
x**2 - 2*x - 1
"""
from sympy.polys.polytools import degree
from sympy.core.function import expand_multinomial
generator = numbered_symbols('a', cls=Dummy)
mapping, symbols, replace = {}, {}, []
def update_mapping(ex, exp, base=None):
a = next(generator)
symbols[ex] = a
if base is not None:
mapping[ex] = a**exp + base
else:
mapping[ex] = exp.as_expr(a)
return a
def bottom_up_scan(ex):
if ex.is_Atom:
if ex is S.ImaginaryUnit:
if ex not in mapping:
return update_mapping(ex, 2, 1)
else:
return symbols[ex]
elif ex.is_Rational:
return ex
elif ex.is_Add:
return Add(*[bottom_up_scan(g) for g in ex.args])
elif ex.is_Mul:
return Mul(*[bottom_up_scan(g) for g in ex.args])
elif ex.is_Pow:
if ex.exp.is_Rational:
if ex.exp < 0 and ex.base.is_Add:
coeff, terms = ex.base.as_coeff_add()
elt, _ = primitive_element(terms, polys=True)
alg = ex.base - coeff
# XXX: turn this into eval()
inverse = invert(elt.gen + coeff, elt).as_expr()
base = inverse.subs(elt.gen, alg).expand()
if ex.exp == -1:
return bottom_up_scan(base)
else:
ex = base**(-ex.exp)
if not ex.exp.is_Integer:
base, exp = (ex.base**ex.exp.p).expand(), Rational(
1, ex.exp.q)
else:
base, exp = ex.base, ex.exp
base = bottom_up_scan(base)
expr = base**exp
if expr not in mapping:
return update_mapping(expr, 1 / exp, -base)
else:
return symbols[expr]
elif ex.is_AlgebraicNumber:
if ex.root not in mapping:
return update_mapping(ex.root, ex.minpoly)
else:
return symbols[ex.root]
raise NotAlgebraic("%s doesn't seem to be an algebraic number" % ex)
def simpler_inverse(ex):
"""
Returns True if it is more likely that the minimal polynomial
algorithm works better with the inverse
"""
if ex.is_Pow:
if (1 / ex.exp).is_integer and ex.exp < 0:
if ex.base.is_Add:
return True
if ex.is_Mul:
hit = True
a = []
for p in ex.args:
if p.is_Add:
return False
if p.is_Pow:
if p.base.is_Add and p.exp > 0:
return False
if hit:
return True
return False
inverted = False
ex = expand_multinomial(ex)
if ex.is_AlgebraicNumber:
return ex.minpoly.as_expr(x)
elif ex.is_Rational:
result = ex.q * x - ex.p
else:
inverted = simpler_inverse(ex)
if inverted:
ex = ex**-1
res = None
if ex.is_Pow and (1 / ex.exp).is_Integer:
n = 1 / ex.exp
res = _minimal_polynomial_sq(ex.base, n, x)
elif _is_sum_surds(ex):
res = _minimal_polynomial_sq(ex, S.One, x)
if res is not None:
result = res
if res is None:
bus = bottom_up_scan(ex)
F = [x - bus] + list(mapping.values())
G = groebner(F, list(symbols.values()) + [x], order='lex')
_, factors = factor_list(G[-1])
# by construction G[-1] has root `ex`
result = _choose_factor(factors, x, ex)
if inverted:
result = _invertx(result, x)
if result.coeff(x**degree(result, x)) < 0:
result = expand_mul(-result)
return result
def _eval_nseries(self, x, n, logx):
# NOTE! This function is an important part of the gruntz algorithm
# for computing limits. It has to return a generalized power
# series with coefficients in C(log, log(x)). In more detail:
# It has to return an expression
# c_0*x**e_0 + c_1*x**e_1 + ... (finitely many terms)
# where e_i are numbers (not necessarily integers) and c_i are
# expressions involving only numbers, the log function, and log(x).
from sympy import powsimp, collect, exp, log, O, ceiling
b, e = self.args
if e.is_Integer:
if e > 0:
# positive integer powers are easy to expand, e.g.:
# sin(x)**4 = (x-x**3/3+...)**4 = ...
return expand_multinomial(self.func(b._eval_nseries(x, n=n,
logx=logx), e), deep=False)
elif e is S.NegativeOne:
# this is also easy to expand using the formula:
# 1/(1 + x) = 1 - x + x**2 - x**3 ...
# so we need to rewrite base to the form "1+x"
nuse = n
cf = 1
try:
ord = b.as_leading_term(x)
cf = C.Order(ord, x).getn()
if cf and cf.is_Number:
nuse = n + 2*ceiling(cf)
else:
cf = 1
except NotImplementedError:
pass
b_orig, prefactor = b, O(1, x)
while prefactor.is_Order:
nuse += 1
b = b_orig._eval_nseries(x, n=nuse, logx=logx)
prefactor = b.as_leading_term(x)
# express "rest" as: rest = 1 + k*x**l + ... + O(x**n)
rest = expand_mul((b - prefactor)/prefactor)
if rest.is_Order:
return 1/prefactor + rest/prefactor + O(x**n, x)
k, l = rest.leadterm(x)
if l.is_Rational and l > 0:
pass
elif l.is_number and l > 0:
l = l.evalf()
elif l == 0:
k = k.simplify()
if k == 0:
# if prefactor == w**4 + x**2*w**4 + 2*x*w**4, we need to
# factor the w**4 out using collect:
return 1/collect(prefactor, x)
else:
raise NotImplementedError()
else:
raise NotImplementedError()
if cf < 0:
cf = S.One/abs(cf)
try:
dn = C.Order(1/prefactor, x).getn()
if dn and dn < 0:
pass
else:
dn = 0
except NotImplementedError:
dn = 0
terms = [1/prefactor]
for m in xrange(1, ceiling((n - dn)/l*cf)):
new_term = terms[-1]*(-rest)
if new_term.is_Pow:
new_term = new_term._eval_expand_multinomial(
deep=False)
else:
new_term = expand_mul(new_term, deep=False)
terms.append(new_term)
terms.append(O(x**n, x))
return powsimp(Add(*terms), deep=True, combine='exp')
else:
# negative powers are rewritten to the cases above, for
# example:
# sin(x)**(-4) = 1/( sin(x)**4) = ...
# and expand the denominator:
nuse, denominator = n, O(1, x)
while denominator.is_Order:
denominator = (b**(-e))._eval_nseries(x, n=nuse, logx=logx)
nuse += 1
if 1/denominator == self:
return self
# now we have a type 1/f(x), that we know how to expand
return (1/denominator)._eval_nseries(x, n=n, logx=logx)
if e.has(Symbol):
return exp(e*log(b))._eval_nseries(x, n=n, logx=logx)
# see if the base is as simple as possible
bx = b
while bx.is_Pow and bx.exp.is_Rational:
bx = bx.base
if bx == x:
return self
# work for b(x)**e where e is not an Integer and does not contain x
# and hopefully has no other symbols
def e2int(e):
"""return the integer value (if possible) of e and a
flag indicating whether it is bounded or not."""
n = e.limit(x, 0)
unbounded = n.is_unbounded
if not unbounded:
# XXX was int or floor intended? int used to behave like floor
# so int(-Rational(1, 2)) returned -1 rather than int's 0
try:
n = int(n)
except TypeError:
#well, the n is something more complicated (like 1+log(2))
try:
n = int(n.evalf()) + 1 # XXX why is 1 being added?
except TypeError:
pass # hope that base allows this to be resolved
n = _sympify(n)
return n, unbounded
order = O(x**n, x)
ei, unbounded = e2int(e)
b0 = b.limit(x, 0)
if unbounded and (b0 is S.One or b0.has(Symbol)):
# XXX what order
if b0 is S.One:
resid = (b - 1)
if resid.is_positive:
return S.Infinity
elif resid.is_negative:
return S.Zero
raise ValueError('cannot determine sign of %s' % resid)
return b0**ei
if (b0 is S.Zero or b0.is_unbounded):
if unbounded is not False:
return b0**e # XXX what order
if not ei.is_number: # if not, how will we proceed?
raise ValueError(
'expecting numerical exponent but got %s' % ei)
nuse = n - ei
if e.is_real and e.is_positive:
lt = b.as_leading_term(x)
# Try to correct nuse (= m) guess from:
# (lt + rest + O(x**m))**e =
# lt**e*(1 + rest/lt + O(x**m)/lt)**e =
# lt**e + ... + O(x**m)*lt**(e - 1) = ... + O(x**n)
try:
cf = C.Order(lt, x).getn()
nuse = ceiling(n - cf*(e - 1))
except NotImplementedError:
pass
bs = b._eval_nseries(x, n=nuse, logx=logx)
terms = bs.removeO()
if terms.is_Add:
bs = terms
lt = terms.as_leading_term(x)
# bs -> lt + rest -> lt*(1 + (bs/lt - 1))
return ((self.func(lt, e) * self.func((bs/lt).expand(), e).nseries(
x, n=nuse, logx=logx)).expand() + order)
if bs.is_Add:
from sympy import O
# So, bs + O() == terms
c = Dummy('c')
res = []
for arg in bs.args:
if arg.is_Order:
arg = c*arg.expr
res.append(arg)
bs = Add(*res)
rv = (bs**e).series(x).subs(c, O(1, x))
rv += order
return rv
rv = bs**e
if terms != bs:
rv += order
return rv
# either b0 is bounded but neither 1 nor 0 or e is unbounded
# b -> b0 + (b-b0) -> b0 * (1 + (b/b0-1))
o2 = order*(b0**-e)
z = (b/b0 - 1)
o = O(z, x)
#r = self._compute_oseries3(z, o2, self.taylor_term)
if o is S.Zero or o2 is S.Zero:
unbounded = True
else:
if o.expr.is_number:
e2 = log(o2.expr*x)/log(x)
else:
e2 = log(o2.expr)/log(o.expr)
n, unbounded = e2int(e2)
if unbounded:
# requested accuracy gives infinite series,
# order is probably non-polynomial e.g. O(exp(-1/x), x).
r = 1 + z
else:
l = []
g = None
for i in xrange(n + 2):
g = self._taylor_term(i, z, g)
g = g.nseries(x, n=n, logx=logx)
l.append(g)
r = Add(*l)
return expand_mul(r*b0**e) + order
def minimal_polynomial(ex, x=None, **args):
"""
Computes the minimal polynomial of an algebraic number.
Examples
========
>>> from sympy import minimal_polynomial, sqrt
>>> from sympy.abc import x
>>> minimal_polynomial(sqrt(2), x)
x**2 - 2
>>> minimal_polynomial(sqrt(2) + sqrt(3), x)
x**4 - 10*x**2 + 1
"""
from sympy.polys.polytools import degree
from sympy.core.function import expand_mul, expand_multinomial
from sympy.simplify.simplify import _is_sum_surds
generator = numbered_symbols("a", cls=Dummy)
mapping, symbols, replace = {}, {}, []
ex = sympify(ex)
if x is not None:
x, cls = sympify(x), Poly
else:
x, cls = Dummy("x"), PurePoly
def update_mapping(ex, exp, base=None):
a = generator.next()
symbols[ex] = a
if base is not None:
mapping[ex] = a ** exp + base
else:
mapping[ex] = exp.as_expr(a)
return a
def bottom_up_scan(ex):
if ex.is_Atom:
if ex is S.ImaginaryUnit:
if ex not in mapping:
return update_mapping(ex, 2, 1)
else:
return symbols[ex]
elif ex.is_Rational:
return ex
elif ex.is_Add:
return Add(*[bottom_up_scan(g) for g in ex.args])
elif ex.is_Mul:
return Mul(*[bottom_up_scan(g) for g in ex.args])
elif ex.is_Pow:
if ex.exp.is_Rational:
if ex.exp < 0 and ex.base.is_Add:
coeff, terms = ex.base.as_coeff_add()
elt, _ = primitive_element(terms, polys=True)
alg = ex.base - coeff
# XXX: turn this into eval()
inverse = invert(elt.gen + coeff, elt).as_expr()
base = inverse.subs(elt.gen, alg).expand()
if ex.exp == -1:
return bottom_up_scan(base)
else:
ex = base ** (-ex.exp)
if not ex.exp.is_Integer:
base, exp = (ex.base ** ex.exp.p).expand(), Rational(1, ex.exp.q)
else:
base, exp = ex.base, ex.exp
base = bottom_up_scan(base)
expr = base ** exp
if expr not in mapping:
return update_mapping(expr, 1 / exp, -base)
else:
return symbols[expr]
elif ex.is_AlgebraicNumber:
if ex.root not in mapping:
return update_mapping(ex.root, ex.minpoly)
else:
return symbols[ex.root]
raise NotAlgebraic("%s doesn't seem to be an algebraic number" % ex)
def simpler_inverse(ex):
"""
Returns True if it is more likely that the minimal polynomial
algorithm works better with the inverse
"""
if ex.is_Pow:
if (1 / ex.exp).is_integer and ex.exp < 0:
if ex.base.is_Add:
return True
if ex.is_Mul:
hit = True
a = []
for p in ex.args:
if p.is_Add:
return False
if p.is_Pow:
if p.base.is_Add and p.exp > 0:
return False
if hit:
return True
return False
polys = args.get("polys", False)
prec = args.pop("prec", 10)
inverted = False
ex = expand_multinomial(ex)
if ex.is_AlgebraicNumber:
if not polys:
return ex.minpoly.as_expr(x)
else:
return ex.minpoly.replace(x)
elif ex.is_Rational:
result = ex.q * x - ex.p
else:
inverted = simpler_inverse(ex)
if inverted:
ex = ex ** -1
res = None
if ex.is_Pow and (1 / ex.exp).is_Integer:
n = 1 / ex.exp
res = _minimal_polynomial_sq(ex.base, n, x, prec)
elif _is_sum_surds(ex):
res = _minimal_polynomial_sq(ex, S.One, x, prec)
if res is not None:
result = res
if res is None:
bus = bottom_up_scan(ex)
F = [x - bus] + mapping.values()
G = groebner(F, symbols.values() + [x], order="lex")
_, factors = factor_list(G[-1])
# by construction G[-1] has root `ex`
result = _choose_factor(factors, x, ex, prec)
if result is None:
raise NotImplementedError("multiple candidates for the minimal polynomial of %s" % ex)
if inverted:
result = expand_mul(x ** degree(result) * result.subs(x, 1 / x))
if result.coeff(x ** degree(result)) < 0:
result = expand_mul(-result)
if polys:
return cls(result, x, field=True)
else:
return result
